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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.

bioinformatics↗
DOE OSTI2024

Statistical Analysis of Fermilab’s Safety Data

In the past ten months, since the Safety and Security pauses of May 31$^{st}$ and June 29$^{th}$ of 2023, there has been an increase in the number of Total Recordable Counts to the point that there are already more incidents in ten months that at any given year in the past decade. The purpose of this study is to try to determine if this increase could be explained as a statistical fluctuation. We will show that it is very unlikely (essentially 4$\sigma$ unlikely) that the increase is a fluctuation, and therefore there must be a cause. The Safety and Security pauses of the past May and June, and many events thereafter, have been impactful events at Fermilab, so we should feel an obligation to assess their benefit, or detriment, to the safety of our people.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Statistical analysis on random quantum circuit sampling by Sycamore and Zuchongzhi quantum processors

Random quantum circuit sampling, a task to sample bit strings from a random quantum circuit, is considered a suitable benchmark task to demonstrate the outperformance of quantum computers even with noisy qubits. Recently, random quantum circuit sampling was performed on the Sycamore quantum processor with 53 qubits [Nature (London) 574, 505 (2019)] and on the Zuchongzhi quantum processor with 56 qubits [Phys. Rev. Lett. 127, 180501 (2021)]. Here, we analyze and compare the statistical properties of the outputs of the random quantum circuit sampling by the Sycamore and Zuchongzhi processors. Using the Marchenko-Pastur law of random matrices of bit strings and the Wasssertein distances between bit strings, we find that the statistical properties of Sycamore bit strings are quite different from those of Zuchongzhi bit strings, while both processors score similar values of linear cross-entropy fidelity for random circuit sampling. Some bit strings sampled by the Zuchongzhi processor pass the NIST random number tests while both Sycamore and Zuchongzhi processors show similar patterns in the heat maps of bit strings. Zuchongzhi bit strings are much closer to classical uniform random bits than those of Sycamore. It is shown that the statistical properties of bit strings of both random quantum circuits change little as the depth of the random quantum circuits increases. Our findings raise a question about the computational reliability of noisy quantum processors because two quantum processors with similar noise levels and similar qubit structures produced statistically different outputs for the same random quantum circuit sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

TU-FG-201-03: Automatic Pre-Delivery Verification Using Statistical Analysis of Consistencies in Treatment Plan Parameters by the Treatment Site and Modality

Purpose: A novel computer software system, namely APDV (Automatic Pre-Delivery Verification), has been developed for verifying patient treatment plan parameters right prior to treatment deliveries in order to automatically detect and prevent catastrophic errors. Methods: APDV is designed to continuously monitor new DICOM plan files on the TMS computer at the treatment console. When new plans to be delivered are detected, APDV checks the consistencies of plan parameters and high-level plan statistics using underlying rules and statistical properties based on given treatment site, technique and modality. These rules were quantitatively derived by retrospectively analyzing all the EBRT treatment plans of the past 8 years at authors’ institution. Therapists and physicists will be notified with a warning message displayed on the TMS computer if any critical errors are detected, and check results, confirmation, together with dismissal actions will be saved into database for further review. Results: APDV was implemented as a stand-alone program using C# to ensure required real time performance. Mean values and standard deviations were quantitatively derived for various plan parameters including MLC usage, MU/cGy radio, beam SSD, beam weighting, and the beam gantry angles (only for lateral targets) per treatment site, technique and modality. 2D-based rules of combined MU/cGy ratio and averaged SSD values were also derived using joint probabilities of confidence error ellipses. The statistics of these major treatment plan parameters quantitatively evaluate the consistency of any treatment plans which facilitates automatic APDV checking procedures. Conclusion: APDV could be useful in detecting and preventing catastrophic errors immediately before treatment deliveries. Future plan including automatic patient identify and patient setup checks after patient daily images are acquired by the machine and become available on the TMS computer. This project is supported by the Agency for Healthcare Research and Quality (AHRQ) under award 1R01HS0222888. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis

Abstract Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb‐makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave‐one‐out cross‐validation. Averaging the classification accuracies for the two LDA‐based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

Ommen, Danica M.↗
DOE OSTI2013

Statistical Analysis of the Phase 3 Emissions Data Collected in the EPAct/V2/E89 Program: January 7, 2010 - July 6, 2012

Phase 3 of the EPAct/V2/E-89 Program investigated the effects of 27 program fuels and 15 program vehicles on exhaust emissions and fuel economy. All vehicles were tested over the California Unified Driving Cycle (LA-92) at 75 degrees F. The program fuels differed on T50, T90, ethanol, Reid vapor pressure, and aromatics. The vehicles tested were new, low-mileage 2008 model year Tier 2 vehicles. A total of 956 test runs were made. Comprehensive statistical modeling and analyses were conducted on methane, carbon dioxide, carbon monoxide, fuel economy, non-methane hydrocarbons, non-methane organic gases, oxides of nitrogen, particulate matter, and total hydrocarbons. In general, model fits determined that emissions and fuel economy were complicated by functions of the five fuel parameters. An extensive evaluation of alternative model fits produced a number of competing model fits. Many of these alternative fits produce similar estimates of mean emissions for the 27 program fuels but should be carefully evaluated for use with emerging fuels with combinations of fuel parameters not included here. The program includes detailed databases on each of the 27 program fuels on each of the 15 vehicles and on each of the vehicles on each of the program fuels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Magnetic imaging and statistical analysis of the metamagnetic phase transition of FeRh with electron spins in diamond

Magnetic imaging based on nitrogen-vacancy (NV) centers in diamond has emerged as a powerful tool for probing magnetic phenomena in fields ranging from biology to physics. A key strength of NV sensing is its local-probe nature, enabling high-resolution spatial images of magnetic stray fields emanating from a sample. However, this local character can also form a drawback for analyzing the global properties of a system, such as a phase transition temperature. Here, we address this challenge by using statistical analyses of magnetic-field maps to characterize the first-order temperature-driven metamagnetic phase transition from the antiferromagnetic to the ferromagnetic state in FeRh. After imaging the phase transition and identifying the regimes of nucleation, growth, and coalescence of ferromagnetic domains, we statistically characterize the spatial magnetic-field maps to extract the transition temperature and thermal hysteresis width. By analyzing the spatial correlations of the maps in relation to the magnetocrystalline anisotropy and external magnetic field, we detect a reorientation of domain walls across the phase transition. The employed statistical approach can be extended to the study of other magnetic phenomena with NV magnetometry or other sensing techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Statistical analysis of dose heterogeneity in circulating blood: Implications for sequential methods of total body irradiation

Purpose: Improvements in delivery techniques for total body irradiation (TBI) using Tomotherapy and intensity modulated radiation therapy have been proven feasible. Despite the promise of improved dose conformality, the application of these ''sequential'' techniques has been hampered by concerns over dose heterogeneity to circulating blood. The present study was conducted to provide quantitative evidence regarding the potential clinical impact of this heterogeneity. Methods: Blood perfusion was modeled analytically as possessing linear, sinusoidal motion in the craniocaudal dimension. The average perfusion period for human circulation was estimated to be approximately 78 s. Sequential treatment delivery was modeled as a Gaussian-shaped dose cloud with a 10 cm length that traversed a 183 cm patient length at a uniform speed. Total dose to circulating blood voxels was calculated via numerical integration and normalized to 2 Gy per fraction. Dose statistics and equivalent uniform dose (EUD) were calculated for relevant treatment times, radiobiological parameters, blood perfusion rates, and fractionation schemes. The model was then refined to account for random dispersion superimposed onto the underlying periodic blood flow. Finally, a fully stochastic model was developed using binomial and trinomial probability distributions. These models allowed for the analysis of nonlinear sequential treatment modalities and treatment designs that incorporate deliberate organ sparing. Results: The dose received by individual blood voxels exhibited asymmetric behavior that depended on the coherence among the blood velocity, circulation phase, and the spatiotemporal characteristics of the irradiation beam. Heterogeneity increased with the perfusion period and decreased with the treatment time. Notwithstanding, heterogeneity was less than {+-}10% for perfusion periods less than 150 s. The EUD was compromised for radiosensitive cells, long perfusion periods, and short treatment times. However, the EUD was unaffected (within 10%) for perfusion periods of less than 150 s or treatment times of 20 min or greater. Treatment over six fractions improved the EUD per fraction such that all parametric combinations resulted in unaffected EUD. The stochastic models confirmed these results. Conclusions: Dose heterogeneity in circulating blood cells is clinically acceptable for typical treatment times, perfusion rates, and cell types. Development of conformal, sequential TBI treatment techniques should not be withheld based on concerns over circulating blood dose heterogeneity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Design and Construction of a High-Resolution Hodoscope for the GlueX Experiment with High-Statistics Analysis of the p0, ¿, and ¿1 Photoproduction Cross Sections from the RadPhi Experiment

Differential cross sections for forward-angle photoproduction of p0, ¿, and ¿ 1 pseudoscalar mesons were measured using data from the RadPhi experiment conducted in Hall B at Jef ferson Lab. RadPhi utilized a tagged bremsstrahlung photon beam incident on a stationary 9Be target, with a detector system configured to trigger on a recoil proton in coincidence with multiple neutral showers in the calorimeter. Events were reconstructed and subjected to kinematic constraints, with background suppressed via sideband subtraction guided by Monte Carlo modeling of background contributions. Cross sections were extracted over the photon energy range 4.4– 5.4 GeV and binned in invariant momentum transfer t, providing measurements from one of the first high-statistics experiments of forward ¿ and ¿1 pro duction from a nuclear target at these energies. Acceptance corrections were applied using a detailed GEANT-based simulation of the detector geometry and response. The resulting cross sections are consistent with 2020 CLAS results, when scaled by the number of protons in beryllium, and show broad agreement with other data and theoretical models. In parallel, a high-resolution photon tagger detector, the Tagger Microscope (TAGM), was designed, constructed, and commissioned for the GlueX experiment in Hall D at Jefferson Lab. The TAGM was developed to provide high-rate tagging capability in the coherent bremsstrahlung peak by detecting post-bremsstrahlung electrons across a one GeV range along the focal plane of the tagging spectrometer. The detector consists of a 5ˆ102 array of 2ˆ2 mm2 square BCF-20 plastic scintillating fibers thermally fused to BCF-98 light guide fibers optically coupled to silicon photomultipliers. These fibers are mounted in a precision machined framework enabling fine positional adjustments to maintain precise alignment with post-bremsstrahlung electron trajectories, while ensuring mechanical rigidity, thermal stability, optical isolation, minimal inactive area, and radiation shielding for electronics. The construction effort involved extensive testing of fiber quality, light transmission, thermal fusing, radiation hardness, and defect analysis using SEM and EDX techniques. Following its installation and commissioning, the TAGM became a critical component of the GlueX beamline, enabling high-rate tagging essential for studies of hybrid mesons and gluonic ex citations.

McIntyre, James [Univ. of Connecticut, Storrs, CT ↗
DOE OSTI2022

Single Gaussian process method for arbitrary tokamak regimes with a statistical analysis

Abstract Gaussian process regression is a Bayesian method for inferring profiles based on input data. The technique is increasing in popularity in the fusion community due to its many advantages over traditional fitting techniques including intrinsic uncertainty quantification and robustness to over-fitting. This work investigates the use of a new method, the change-point method, for handling the varying length scales found in different tokamak regimes. The use of the Student’s t-distribution for the Bayesian likelihood probability is also investigated and shown to be advantageous in providing good fits in profiles with many outliers. To compare different methods, synthetic data generated from analytic profiles is used to create a database enabling a quantitative statistical comparison of which methods perform the best. Using a full Bayesian approach with the change-point method, Matérn kernel for the prior probability, and Student’s t-distribution for the likelihood is shown to give the best results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Nanotomographic observation and statistical analysis of overcharging induced cracks in LiCoO 2 single crystalline particles

Particle fracture represents an important mode of battery electrode degradation. Extensive cracking occurs in the layered oxide cathodes of lithium-ion rechargeable batteries when they are charged beyond safe operational voltages. In this paper, we analyze the morphology and distribution of cracks in over 100 overcharged LiCoO 2 (LCO) single-crystalline particles imaged via X-ray nanotomography. Herein, we observe a strong particle size dependence in both nucleation and growth of cracks, with percentage of cracked particles, crack size, and crack surface area per unit volume all increasing significantly with particle volume. Increasing the cutoff voltage above 4.6V is found to trigger much more pronounced crack growth, which we attribute to the large misfit stress caused by the H1-3 to O1 phase transition. This study offers valuable statistical insights into the fracture behavior of layered oxide cathodes and reveals the importance of particle size control on electromechanical degradation of battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2011

Statistical analysis of high power microwave surface flashover delay times in nitrogen with metallic field enhancements

The physical mechanisms that contribute to atmospheric breakdown induced by high power microwaves (HPMs) are of particular interest for the further development of high power microwave systems and related technologies. For a system in which HPM is produced in a vacuum environment for the purpose of radiating into atmosphere, it is necessary to separate the atmospheric environment from the vacuum environment with a dielectric interface. Breakdown across this interface on the atmospheric side and plasma development to densities prohibiting further microwave propagation are of special interest. In this paper, the delay time between microwave application and plasma emergence is investigated. Various external parameters, such as UV illumination or the presence of small metallic points on the surface, provide sources for electron field emission and influence the delay time which yields crucial information on the breakdown mechanisms involved. Due to the inherent statistical appearance of initial electrons and the statistics of the charge carrier amplification mechanisms, the flashover delay times deviate by as much as {+-}50% from the average, for the investigated case of discharges in N{sub 2} at pressures of 60-140 Torr and a microwave frequency of 2.85 GHz with 3 {mu}s pulse duration, 50 ns pulse risetime, and MW/cm{sup 2} power densities. The statistical model described in this paper demonstrates how delay times for HPM surface flashover events can be effectively predicted for various conditions given sufficient knowledge about ionization rate coefficients as well as the production rate for breakdown initiating electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Statistical Analysis of the Eigenmode Spectrum in the SRF Cavities with Mechanical Imperfections

The superconducting radio frequency (SRF) technology is progressing rapidly over last decades toward high accelerating gradients and low surface resistance making feasible the particle accelerators operation with high beam currents and long duty factors. However, the coherent RF losses due to high order modes (HOMs) excitation becomes a limiting factor for these regimes. In spite of the operating mode, which is tuned separately, the parameters of HOMs vary from one cavity to another due to finite mechanical tolerances during cavities fabrication. It is vital to know in advance the spread of HOM parameters in order to predict unexpected cryogenic losses, overheating of beam line components and to keep stable beam dynamics. In this paper we present the method of generating the unique cavity geometry with imperfections while preserving operating mode frequency and field flatness. Based on the eigenmode spectrum calculation of series of randomly generated cavities we can accumulate the data for the evaluation the HOM statistics. Finally, we describe the procedure for the estimation of the probability of the resonant HOM losses in the SRF resonators. The study of these effects leads to specifications of SC cavity and cryomodule and can significantly impact on the efficiency and reliability of the machine operation

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Remote sensing and statistical analysis of the effects of hurricane María on the forests of Puerto Rico

Widely recognized as one of the worst natural disaster in Puerto Rico's history, hurricane María made landfall on September 20, 2017 in southeast Puerto Rico as a high-end category 4 hurricane on the Saffir-Simpson scale causing widespread destruction, fatalities and forest disturbance. This study focused on hurricane María's effect on Puerto Rico's forests as well as the effect of landform and forest characteristics on observed disturbance patterns. In this work, we used Google Earth Engine (GEE) to assess the severity of forest disturbance using a disturbance metric based on Landsat 8 satellite data composites with pre and post-hurricane María. Forest structure, tree phenology characteristics, and landforms were obtained from satellite data products, including digital elevation model and global forest canopy height. Our analyses showed that forest structure, and characteristics such as forest age and forest type affected patterns of forest disturbance. Among forest types, highest disturbance values were found in sierra palm, transitional, and tall cloud forests; seasonal evergreen forests with coconut palm; and mangrove forests. For landforms, greatest disturbance metrics was found at high elevations, steeper slopes, and windward surfaces. As expected, high levels of disturbance were also found close to the hurricane track, with disturbance less severe as hurricane María moved inland. Results demonstrated that forest and landform characteristics accounted for 34% of the variation in spatial forest spectral disturbance patterns. This study demonstrated an informative regional approach, combining remote sensing with statistical analyses to investigate factors that result in variability in hurricane effects on forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Statistical analysis and degradation pathway modeling of photovoltaic minimodules with varied packaging strategies

Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power loss in these glass/backsheet PV minimodules. We show successful implementation of netSEM to elucidate the relationships between variables in PV systems and predict a specific service lifetime. The results from pairwise relationships and multiple regression show consistency. This work presents a greater opportunity to be expanded to other materials systems.

electrical measurements↗
DOE OSTI2014

A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography–mass spectrometry

Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentified metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Statistical analysis of MMS observations of energetic electron escape observed at/beyond the dayside magnetopause

Here, observations from the Energetic Particle Detector (EPD) instrument suite aboard the Magnetospheric Multiscale (MMS) spacecraft show that energetic (greater than tens of keV) magnetospheric particle escape into the magnetosheath occurs commonly across the dayside. This includes the surprisingly frequent observation of magnetospheric electrons in the duskside magnetosheath, an unexpected result given assumptions regarding magnetic drift shadowing. The 238 events identified in the 40 keV electron energy channel during the first MMS dayside season that exhibit strongly anisotropic pitch angle distributions indicating monohemispheric field-aligned streaming away from the magnetopause. A review of the extremely rich literature of energetic electron observations beyond the magnetopause is provided to place these new observations into historical context. Despite the extensive history of such research, these new observations provide a more comprehensive data set that includes unprecedented magnetic local time (MLT) coverage of the dayside equatorial magnetopause/magnetosheath. These data clearly highlight the common escape of energetic electrons along magnetic field lines concluded to have been reconnected across the magnetopause. While these streaming escape events agree with prior studies which show strong correlation with geomagnetic activity (suggesting a magnetotail source) and occur most frequently during periods of southward IMF, the high number of duskside events is unexpected and previously unobserved. Although the lowest electron energy channel was the focus of this study, the events reported here exhibit pitch angle anisotropies indicative of streaming up to 200 keV, which could represent the magnetopause loss of >1 MeV electrons from the outer radiation belt.

58 GEOSCIENCES↗
DOE OSTI2021

How Useful are Conventional I–Vs for Performance Calibration of Single- and Two-Junction Perovskite Solar Cells? A Statistical Analysis of Performance Data on ≈200 Cells from 30 Global Sources

As perovskite photovoltaics (PV) advance from the laboratory to commercial prototypes, their accurate and reliable performance testing is becoming increasingly important. The well-documented dynamic response of perovskite solar cells to an external applied voltage has led to the development of steady-state performance measurement methods; however, these methods have not been widely adopted by the perovskite PV community. A key reason for this is that steady-state measurement methods take tens of minutes to complete, as opposed to conventional "fast" current-voltage (I-V) measurements usually lasting a few seconds. Fast I-Vs arise from a snapshot, almost always not a steady-state condition of the device; however, given their widespread use, the question arises: how do performance parameters of perovskite PV compare when measured with fast I-V and with a steady-state method? Results compiled from approximately 200 perovskite PV cells, including single junction, and two-terminal perovskite-perovskite and perovskite-Si tandems, show that fast I-Vs can provide a useful measure of the open-circuit voltage of the devices, while the short-circuit current and the overall efficiency can be widely misestimated. Here, the implications of these findings on performance testing protocols are discussed and possible options for fast and accurate testing of perovskite PV are proposed.

14 SOLAR ENERGY↗